Senior Technology Engineer - Data Science Platform (DSP)

Role Overview

Requirements

• **Key Responsibilities****Platform Engineering & Operations*** Own end-to-end **technical operations of DSP infrastructure**
• Ensure **high availability, performance, and scalability** of platform services
• Monitor system health, troubleshoot issues, and implement permanent fixes (not patchwork)
• **Automation & Orchestration*** Design and implement **automation frameworks** to eliminate manual processes
• Build **CI/CD pipelines** and automate deployment workflows
• Drive **infrastructure-as-code (IaC)** adoption using tools like Terraform/Ansible
• **Container & Cloud Platform Management*** Manage and optimize **OpenShift / Kubernetes environments**
• Work across **multi-cloud (AWS, Azure, GCP)** infrastructure
• Ensure efficient resource utilization and cost optimisation
• **MLOps / Data Platform Support*** Enable smooth **ML model deployment and lifecycle management**
• Support tools like **OpenShift AI, SageMaker, or similar platforms**
• Ensure reproducibility and reliability of data science workflows
• **Monitoring & Reliability*** Implement monitoring using **Prometheus, Grafana, ELK stack**
• Define SLAs, SLOs, and ensure platform meets reliability standards
• Drive proactive incident prevention (not reactive firefighting)
• **Collaboration & Governance*** Work closely with **Data Scientists, DevOps, and Platform teams**
• Ensure adherence to **security, compliance, and governance standards**
• Act as a **technical SME** for DSP operations
• **Mandatory Skills (Non-Negotiable)*** Strong experience in **OpenShift / Kubernetes**
• Hands-on experience in **multi-cloud environments (AWS/Azure/GCP)**
• Expertise in **automation (Terraform, Ansible, Jenkins, GitOps)**
• Strong knowledge of **CI/CD pipelines and DevOps practices**
• Experience in **Python or scripting (Bash/Shell)**
• Experience with **monitoring tools (Prometheus, Grafana, ELK)**
• **Good to Have*** Experience in **MLOps / AI platforms (OpenShift AI, SageMaker, Bedrock)**
• Exposure to **LLM deployment / inference platforms (vLLM, Triton, etc.)**
• Knowledge of **data pipelines and big data ecosystems**
• Banking or financial services experience
• **Experience Required*** **6–10 years** of relevant experience in Platform Engineering / DevOps / Cloud Engineering
• Proven experience managing **enterprise-scale platforms**